Grainy axial datasets
The following question has been sent by Judy Oltmann, CTA Technologist, USA:
Grainy axial datasets: In trial patients using the Definition, the clarity of the axial datasets has been a constant complaint. Using an ROI to measure the pixel density, the 64 slice has a marked improvement over the Definition of almost 50 % more in pixel density. Has this been an issue anywhere else?
Dr. Savvas Nicolaou and colleague, Vancouver General Hospital, University of British Columbia:
This is highly dependent on the body region being scanned. We have seen this in the brain but no difference than the single source 64 slice scanner.
- What I would say, if you are using 4d care dose you need to look at your quality mAs reference value. If the axials are to grainy you need to increase the quality mAs reference value.
- Are the axials grainy on all body types if not then use a smoother algorithm on big patients and up the quality mAs reference value.
- We have also found the type and volume of contrast makes a difference, if you are doing abdominal imaging increase the volume of contrast and I assume you are already using a saline chaser. For CTA’S increase the rate of injection and increase the concentration ie use a 370 iodine concentration.
I have asked our physicist to also respond, please see his response below:
It is difficult to know from your description whether the problem is one of noise or contrast. Noise can be caused by many factors
What body part is this? What do you mean by pixel density – CT number or noise?
I would need to know the body part, the reconstruction algorithm used, slice thickness, CTDI
If this is a body part measure the noise (standard deviation) within the aorta
Thank you
Dr Savvas Nicolaou
